Komponenten

Komponenten

Item #1

Datenbewusstsein

Lorem ipsum dolor sit amet consectetur adipiscing elit dolor Lorem ipsum dolor sit amet consectetur adipiscing elit dolor Lorem ipsum dolor sit amet consectetur adipiscing elit dolorLorem ipsum dolor sit amet consectetur adipiscing elit dolor

Datenbewusstsein

Lorem ipsum dolor sit amet consectetur adipiscing elit dolor Lorem ipsum dolor sit amet consectetur adipiscing elit dolor Lorem ipsum dolor sit amet consectetur adipiscing elit dolorLorem ipsum dolor sit amet consectetur adipiscing elit dolor Lorem ipsum dolor sit amet consectetur adipiscing elit dolor Lorem ipsum dolor sit amet consectetur adipiscing elit dolor Lorem ipsum dolor sit amet consectetur adipiscing elit dolorLorem ipsum dol
Phase Inhalt Ziele Material
1a

Einführung in den Interaktionskontext und Problematisierung
Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet. Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.

Didaktischer Kommentar
Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.

  • Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua.

  • At vero eos et accusam et justo duo dolores et ea rebum.
Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum.
1a

Einführung in den Interaktionskontext und Problematisierung
Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet. Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.

Didaktischer Kommentar
Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.

  • Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua.

  • At vero eos et accusam et justo duo dolores et ea rebum.
Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum.

Session 15 - Part 1: Josephine Louie (USA)

Supporting critical data literacy for civic engagement and social justice
  • 19.06.2024
  • 16.00-17.00 Uhr
  • (UTC+2)

Session 15 - Part 2: Joachim Engel (Germany)

Critical data literacy for democracy education
  • 19.06.2024
  • 17.10-18.10 Uhr
  • (UTC+2)

Session 13 - Part 1: Vince Geiger (Australia)

Vince Geiger (Australia)
Part 1: Evaluating media claims about sustainability through the use of large data sets
  • 24.01.2024
  • 16.00-17.30 Uhr
  • (UTC+1)

Session 13 - Part 2: Devin W. Silvia (USA)

Devin W. Silvia (USA)
Part 2: A learner-centered approach to teaching computational modeling, data analysis, and programming
  • 24.01.2024
  • 17.30-19.00 Uhr
  • (UTC+1)

Session 14 - Part 1: Ismaila Sanusi (Finland)

The Role of Data in Artificial Intelligence Literacy in school education
  • 17.04.2024
  • 16.00-17.00 Uhr
  • (UTC+2)

Session 14 - Part 2: Yasmin B. Kafai & Luis Morales-Navarro (USA)

High School Youth Peer Auditing of Machine Learning-Powered Applications to Promote Computational Literacies
  • 17.04.2024
  • 17.10-18.10 Uhr
  • (UTC+2)

Session 10 - Part 1: Tor Ole Odden (Norway)

Tor Ole Odden (Norway)
Part 1: Using Computational Essays to Support Student Creativity and Agency in Science - Tor Ole Odden (Norway)
  • 18.01.2023
  • 17.00-19.30 Uhr
  • (UTC+1)

Session 09 - Part 1: Nick Horton (USA)

Nick Horton (USA)
Part 1: Teaching reproducibility and responsible workflows - Nick Horton (USA)
  • 18.01.2023
  • 17.00-18.30 Uhr
  • (UTC+1)

Session 10 - Part 2: Tom Button and Ian Dickerson (UK)

Tom Button and Ian Dickerson (UK)
Part 2: Design decisions in creating short data science courses for pre-university students - Tom Button and Ian Dickerson (UK)
  • 18.01.2023
  • 18.30-19.30 Uhr
  • (UTC+1)

Session 09 - Part 2: Francine Berman (USA)

Francine Berman (USA)
Part 2: Teaching Social Responsibility for a Tech-Powered World - Francine Berman (USA)
  • 18.01.2023
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 11 - Part 1: Martin Frank and Sarah Schönbrodt (Germany)

Martin Frank and Sarah Schönbrodt (Germany)
Part 1: How much mathematical modeling is in AI? - Martin Frank and Sarah Schönbrodt (Germany)
  • 17.05.2023
  • 16.00-17.30 Uhr
  • (UTC+2)

Session 11 - Part 2: Dani Ben-Zvi (Israel)

Dani Ben-Zvi (Israel)
Part 2: Reasoning with Data in School-Based Citizen Science - Dani Ben-Zvi (Israel)
  • 17.05.2023
  • 17.30-19.00 Uhr
  • (UTC+2)

Session 12 - Part 1: Henning Wachsmuth (Germany)

Henning Wachsmuth (Germany)
Part 1: NLP Research in the Age of Large Language Models – Henning Wachsmuth
  • 29.11.202316.00 Uhr
  • 02.06.202217.30 Uhr
  • (UTC+1)

Session 12 - Part 2: Travis Weiland (USA)

Travis Weiland (USA)
Part 2: Reading and Writing the World with Data - Travis Weiland (USA)
  • 29.11.202317.30 Uhr
  • 02.06.202219.00 Uhr
  • (UTC+1)

Session #03

Graham Dove (USA) & Rob Gould (USA)
Part 1: Learning data science through civic engagement with open data - Graham Dove (USA)
Part 2: Why should students take a data science course? - Rob Gould (USA)
  • 02.01.2022
  • 16.00-18.30 Uhr
  • (UTC+1)

Session #04

Arnold Pears (Sweden) & Jim Ridgway (England)
Part 1: Why Computing Education, and Especially CT, Needs a Broader Perspective! - Arnold Pears (Sweden)
Part 2: Education for a fast-changing world: Conceptions of Statistical Literacy and Data Science - Jim Ridgway (England)
  • 01.04.2022
  • 16.00-18.30 Uhr
  • (UTC+2)

Session #05

Lukas Höper and Carsten Schulte (Germany) & Orit Hazzan and Koby Mike (Israel)
Part 1: Data Awareness: Be aware of the data! - Lukas Höper and Carsten Schulte (Germany)
Part 2: Teaching Core Principles of Machine Learning with a Simple Machine Learning Algorithm: The Case of the KNN Algorithm  - Orit Hazzan and Koby Mike (Israel)
  • 18.05.2022
  • 16.00-18.30 Uhr
  • (UTC+2)

Session #06

Marc Hauer (Germany) & Michelle Hoda Wilkerson (USA)
Part 1: My AI discriminates? How could this happen and who is to blame? - Marc Hauer (Germany)
Part 2: A Framework for Exploring the Purposes and Processes of Data Wrangling in Complex Self-Directed Analysis Tasks - Michelle Hoda Wilkerson (USA)
  • 02.06.2022
  • 16.00-18.30 Uhr
  • (UTC+2)

Session 07 - Part 1: Conrad Wolfram (England)

Conrad Wolfram (England)
Part 1: Roadmap to Computational Thinking for the AI age: A challenge for Mathematics and Computer Science Education - Conrad Wolfram (England)
  • 02.11.2022
  • 17.00-18.30 Uhr
  • (UTC+1)

Session 07 - Part 2: Sven Hüsing, Carsten Schulte and Dan Verständig (Germany)

Sven Hüsing, Carsten Schulte and Dan Verständig (Germany)
Part 2: Epistemic Programming and Creative Coding: Programming as an Empowering Means for Self-Expression and Communication - Sven Hüsing, Carsten Schulte and Dan Verständig (Germany)
  • 02.11.2022
  • 18.30-20.00 Uhr
  • (UTC+1)

Session 08 - Part 1: Ute Schmid (Germany)

Ute Schmid (Germany)
Part 1: Learning About and Learning with Artificial Intelligence in School: From Understanding of Basic AI Concepts to Trustworthy and Human-centric AI Tools - Ute Schmid (Germany)
  • 07.12.2022
  • 17.00-18.30 Uhr
  • (UTC+1)

Session 08 - Part 2: Jane Waite (England)

Jane Waite (England)
Part 2: A hands-on workshop to develop a set of potential goals for learning about AI - Jane Waite (England)
  • 07.12.2022
  • 18.30-20.00 Uhr
  • (UTC+1)

Jan Mokros and Bill Finzer (USA)

Data Detective Clubs in the Time of COVID-19
Data Detective Clubs in the Time of COVID-19 - Jan Mokros and Bill Finzer (USA)
  • 27.10.2021
  • 16.00-18.30 Uhr
  • (UTC+1)

Session #01

Jan Mokros and Bill Finzer (USA) & Matti Tedre and Henriikka Vartiainen (Finland)
Part 1: Data Detective Clubs in the Time of COVID-19 - Jan Mokros and Bill Finzer (USA)
Part 2: Teaching machine learning in school: Some emerging research trajectories - Matti Tedre and Henriikka Vartiainen (Finland)
  • 27.10.2021
  • 16.00-18.30 Uhr
  • (UTC+1)

Session #02

Tobias Matzner (Germany) & Rolf Biehler and Yannik Fleischer (Germany)
Part 1: Beyond Bias. Locating questions of injustice in Data Science and Artificial Intelligence - Tobias Matzner (Germany)
Part 2: Bringing together statistics and computer science education: Machine learning by decision trees grounded in students’ data exploration experiences - Rolf Biehler and Yannik Fleischer (Germany)
  • 24.11.2021
  • 16.00-18.30 Uhr
  • (UTC+1)
Aktuell gibt es keine neuen Termine. Wir werden Sie aber in Zukunft hier darüber informieren.

test

Revisiting Fundamental Ideas for Statistics Education From the Perspective of Machine Learning and Its Applications.

Biehler, R. (2023)

In S. A. Peters, L. Zapata-Cardona, F. Bonafini, & A. Fan (Eds.)

Editorial: Research on Data Science Education.

Biehler, R., De Veaux, R., Engel, J., Kazak, S., & Frischemeier, D. (2023)

Test

Max M. (2022)

Test

test 2021

Max M. (2021)

Test

Klicken Sie auf den unteren Button, um den Inhalt von videos.uni-paderborn.de zu laden.

Inhalt laden

Nach oben scrollen